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Impact Tracking

When you make changes to improve your AI visibility, you need to know whether those changes actually worked. Impact Tracking gives you a clear before-and-after picture so you can see exactly what moved the needle.

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How It Works

Impact Tracking follows a simple three-step process:

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1. Baseline Capture

When you start tracking a set of keywords or apply a recommendation, we automatically capture your current performance across all key metrics. This snapshot becomes your “before” measurement.

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2. Continuous Monitoring

Over the following 30 days, we track the same metrics at regular intervals. Every tracking run captures fresh data so you can see trends forming in real time.

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3. Impact Report

At the end of the measurement period, you get a clear report showing what changed, by how much, and whether the change is statistically meaningful.

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What Gets Measured

Impact Tracking monitors six core metrics:
The percentage of tracked AI responses that mention your brand. This is the single most important indicator of your overall AI visibility.
The raw number of times your brand appears across all tracked AI responses. Useful for spotting trends even when SOV stays flat due to market growth.
Where your brand typically appears within an AI response. Being mentioned first carries more weight than being listed fifth.
How often AI responses link back to your website when mentioning your brand. Citations drive direct traffic and signal strong authority.
The difference between your visibility and your closest competitors. Tracks whether you are gaining ground or falling behind relative to others in your market.
How thoroughly and accurately AI platforms describe your brand. A high score means AI responses include rich, relevant details rather than just a passing mention.

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The 30-Day Timeline

Impact Tracking uses a 30-day window by default. Here is why:
  • Days 1-7: AI platforms may not have re-crawled your updated content yet. Early data establishes the baseline.
  • Days 7-14: Changes typically start appearing as AI models incorporate new information.
  • Days 14-30: Trends stabilize and you can see the sustained impact of your changes.
You can start a new impact tracking period at any time. If you make a second round of changes midway through, consider starting a fresh measurement so the data stays clean.

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Trusting the Results

Not all changes in metrics are meaningful. Impact Tracking helps you separate signal from noise:
  • Trend direction: A metric that moves consistently in one direction over multiple data points is more reliable than a single spike.
  • Magnitude: Small fluctuations (under 2-3%) are common and may just reflect normal variation in how AI generates responses.
  • Consistency across queries: If your SOV improves on most tracked keywords rather than just one or two, the improvement is likely real.
AI responses are not deterministic. The same query can produce slightly different answers each time. Impact Tracking accounts for this by averaging across multiple observations rather than relying on single data points.

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Getting Started

  1. Navigate to your workspace dashboard.
  2. Apply a recommendation or make changes to your content.
  3. Impact Tracking begins automatically with your next tracking run.
  4. Check the Impact tab after 7 days for early signals, and again at 30 days for the full picture.